Practical AI Building a career in Data Science
Mar 16, 2020
Emily Robinson, a Senior Data Scientist at Warby Parker and co-author of 'Build a Career in Data Science', shares her expertise on optimizing the job search in data science. She discusses crafting resumes and cover letters that stand out, along with recognizing fair compensation for roles. Emily also highlights the importance of networking and adapting to various career paths, whether in startups or large firms. Her insights into navigating failures and the significance of communication in data-driven environments are invaluable for budding data scientists.
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Importance of Interview Questions
- Robert Chang's first data science role at The Washington Post involved unexpected data engineering work.
- This highlights the importance of asking detailed questions during interviews.
Portfolio and Networking
- Build a portfolio with original projects to stand out from other applicants.
- Networking is essential for landing a data science job.
Focus on Fundamentals
- Focus on fundamental data science skills rather than solely on AI and deep learning.
- Master data manipulation, summarization, visualization, and basic modeling.
